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什么是 RLHF？ RLHF (基于人类反馈的强化学习) 是一种 机器学习 技术，RLHF 利用人类的直接反馈来训练“奖励模型”，然后利用该模型通过强化学习来优化人工智能坐席的性能。 L'apprendimento per rinforzo con feedback umano (rlhf) è una tecnica di machine learning in cui viene addestrato un modello di ricompensa con feedback umano diretto, quindi utilizzato per ottimizzare le prestazioni di un agente di intelligenza artificiale attraverso l'apprendimento per rinforzo. RLHFは通常、エンド・ツー・エンドのトレーニング方法としてではなく、事前トレーニングされたモデルを微調整して最適化に使用されます。 たとえば、InstructGPTはRLHFを使用し、既存のGPT（Generative Pre-trained Transformer）モデルを強化しました。
휴먼 피드백을 통한 강화 학습(RLHF)은 사람의 피드백을 사용하여 AI 에이전트를 최적화하기 위한 '보상 모델'을 학습하는 머신 러닝 기술입니다. Rlhf o aprendizaje por refuerzo a partir de la información humana es una técnica de machine learning en la que se entrena a un modelo de recompensa. Rlhf, también llamado aprendizaje por refuerzo a partir de las preferencias humanas, es especialmente adecuado para tareas con objetivos complejos, mal definidos o difíciles de especificar.
Rlhf é uma técnica de aprendizado de máquina que usa feedback humano para aperfeiçoar os modelos atrvés de aprendizado por reforço.
Le rlhf, également appelé apprentissage par renforcement basé sur les préférences humaines, est particulièrement adapté aux tâches dont les objectifs sont complexes, mal définis ou difficiles à spécifier. Rlhf (reinforcement learning from human feedback) ist eine technik des maschinellen lernens, bei der ein „belohnungsmodell“ durch direktes menschliches feedback trainiert und dann zur optimierung der leistung eines agenten der künstlichen intelligenz durch bestärkendes lernen verwendet wird.
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